The Initial Trade Impact of Brexit : Effect of Exchange Rate Volatility on UK’s Trade

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Added on 2020-10-23

The Initial Trade Impact of Brexit : Effect of Exchange Rate Volatility on UK’s Trade

Added on 2020-10-23

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The Initial Trade Impact of Brexit:Effect of Exchange Rate Volatility onUK’s Trade

TABLE OF CONTENTSStatistical analysis:.................................................................................................................1Panel data................................................................................................................................1Type of data required for panel analysis................................................................................1Reason for application of Panel data......................................................................................2Description of methods...........................................................................................................5Results....................................................................................................................................6REFERENCES................................................................................................................................9

The Initial Trade Impact of Brexit : Effect of Exchange Rate Volatility on UK’s Trade_2

Statistical analysis:Regression is referred as statistical measurement implied in finance, investing along withother disciplines which attempts for determining strength of relationship among single dependentvariable along with series of other altering variables which are replicated as independentvariables. It helps financial and investment managers for valuing asset and understandingrelationship among variables like commodity prices along with stock of business with deal withparticular commodities. Generally, it is used for examining relationship among one dependentand independent variable (Anderson, James and Eric van Wincoop, 2003). After performing thisanalysis, regression statistics could be used for purpose of predicting dependent variable whenindependent variable is known.Panel dataPanel data is considered as type on longitudinal data or data gathered at different point oftime. There are three main types of longitudinal data such as Time series data, polled crosssections and panel data. Time series data comprise many observations as few as single unit suchas trends of stock price and aggregate national statistics. The pooled cross sections is two ormore independent samples of various units which are drawn through same population at variousother time periods. Simultaneously, two of more observations on many units are referred as paneldata (Tinbergen, 1962). The panel data could be analyzed when there is requirement ofdescribing changes over time or for estimating superior trends in social phenomena along withestimation of causal models. Panel data is useful because with observations which span bothindividuals and time in cross sections with availability of more information and gives moreefficient estimates. Its use allows for empirical test for broad range of hypothesis. On basis ofpanel data, one can control unmeasurable and unobserved sources of individual heterogeneitywhich vary across individuals but it does not vary over time. Simultaneously, this will lead toomit variable bias.Type of data required for panel analysisThe basic panel method is in need of at least 2 waves of measurement as in this data setthere is presence of GDP and EIG where panel datasets includes time invariant and time varyingvariables. There is presence of alternative method for structuring data to keep every measures insingle record. Sometimes, it is referred as wide format.1

The Initial Trade Impact of Brexit : Effect of Exchange Rate Volatility on UK’s Trade_3

The estimation techniques for panel models as General linear model is referred asfoundation of estimation of linear panel model such as ordinary least squares, Weighted leastsquares and Generalised least squares (Dell’Aricca, Giovanni, 1999). The least squaresestimation of panel models entails with three steps where first is data transformation of withestimation of first stage, secondly, estimation of parameters with application of ordinary Leastsquares and at last estimation of variance and covariance matrix of estimates.Reason for application of Panel dataPanel data could undertake explicit amount of individual particular heterogeneity asindividual is denoted as micro unit. With combination of data in two dimensions, panel dataprovides various data variation, more degree of freedom along with less collinearity. In thesimilar aspect, panel data is better suited comparatively to cross sectional data for understandingdynamics of alteration. For instance, it is best appropriate for understanding behavior oftransition. It is better for measuring and detecting effects which could not be observed in timeseries or cross section data. It helps in enabling study of models which comprises complexbehavior models such as effect of economic cycles or technological change. Conversely, itminimizes effects of aggregation bias and from aggregating firms in broad groups. In case, allcross sectional units have similar number of observations in time series, then panel is balancedand vice versa.For instance:Estimation of (1) is dependent on assumption what are undertaken related to intercept(a0), a1 as slope coefficient along with error term. There is presence of several assumptionscould be made in order for estimating such as follows:In the first assumption, slope and intercept coefficients are constant across firms and timealong with error term which captures variation over firms and time. In the same series, slopecoefficient is constant but in this context intercept varies over time and firms. Henceforth, all2

The Initial Trade Impact of Brexit : Effect of Exchange Rate Volatility on UK’s Trade_4

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The Initial Trade Impact of Brexit : Effect of Exchange Rate Volatility on UK’s Trade